OpenML
Supervised Classification on Click_prediction_small

Supervised Classification on Click_prediction_small

Task 7295 Supervised Classification Click_prediction_small 39610 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1851.3688, total_cost: 672800, usercpu_time_millis: 0.433, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6239, average_cost: 16.7936, f_measure: 0.7562, kappa: 0.0046, kb_relative_information_score: -3150.761, mean_absolute_error: 0.2732, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8166, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9752, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3694, root_relative_squared_error: 0.9871, scimark_benchmark: 1851.3287, total_cost: 670870, usercpu_time_millis: 1.147, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 1.1,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1838.6023, total_cost: 672800, usercpu_time_millis: 0.451, usercpu_time_millis_testing: 0.052, usercpu_time_millis_training: 0.399,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1842.6679, total_cost: 672800, usercpu_time_millis: 0.449, usercpu_time_millis_testing: 0.055, usercpu_time_millis_training: 0.394,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6173, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1702.1624, mean_absolute_error: 0.278, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.372, root_relative_squared_error: 0.994, scimark_benchmark: 1848.2615, total_cost: 672800, usercpu_time_millis: 0.501, usercpu_time_millis_testing: 0.053, usercpu_time_millis_training: 0.448,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1846.2342, total_cost: 672800, usercpu_time_millis: 0.449, usercpu_time_millis_testing: 0.054, usercpu_time_millis_training: 0.395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1850.8185, total_cost: 672800, usercpu_time_millis: 0.459, usercpu_time_millis_testing: 0.055, usercpu_time_millis_training: 0.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1846.6923, total_cost: 672800, usercpu_time_millis: 0.445, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.396,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.625, average_cost: 16.7858, f_measure: 0.7564, kappa: 0.0054, kb_relative_information_score: -3116.1615, mean_absolute_error: 0.2731, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8255, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.975, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.9869, scimark_benchmark: 1842.6679, total_cost: 670560, usercpu_time_millis: 0.726, usercpu_time_millis_testing: 0.056, usercpu_time_millis_training: 0.67,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1843.6588, total_cost: 672800, usercpu_time_millis: 0.421, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1849.7595, total_cost: 672800, usercpu_time_millis: 0.467, usercpu_time_millis_testing: 0.052, usercpu_time_millis_training: 0.415,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1845.1352, total_cost: 672800, usercpu_time_millis: 0.452, usercpu_time_millis_testing: 0.053, usercpu_time_millis_training: 0.399,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1850.2875, total_cost: 672800, usercpu_time_millis: 0.462, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 0.411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1848.2615, total_cost: 672800, usercpu_time_millis: 0.465, usercpu_time_millis_testing: 0.054, usercpu_time_millis_training: 0.411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5768, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -563.1775, mean_absolute_error: 0.2796, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9981, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3736, root_relative_squared_error: 0.9983, scimark_benchmark: 1842.6679, total_cost: 672800, usercpu_time_millis: 0.495, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 0.445,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1851.8567, total_cost: 672800, usercpu_time_millis: 0.423, usercpu_time_millis_testing: 0.048, usercpu_time_millis_training: 0.375,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1850.2875, total_cost: 672800, usercpu_time_millis: 0.421, usercpu_time_millis_testing: 0.045, usercpu_time_millis_training: 0.376,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1843.1261, total_cost: 672800, usercpu_time_millis: 0.44, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 0.389,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1843.1261, total_cost: 672800, usercpu_time_millis: 0.456, usercpu_time_millis_testing: 0.054, usercpu_time_millis_training: 0.402,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1842.6679, total_cost: 672800, usercpu_time_millis: 0.422, usercpu_time_millis_testing: 0.044, usercpu_time_millis_training: 0.378,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1844.6953, total_cost: 672800, usercpu_time_millis: 0.434, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 0.384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1841.5689, total_cost: 672800, usercpu_time_millis: 0.429, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 0.379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6232, average_cost: 16.8031, f_measure: 0.756, kappa: 0.0037, kb_relative_information_score: -3156.8513, mean_absolute_error: 0.2734, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8201, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.976, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3695, root_relative_squared_error: 0.9874, scimark_benchmark: 1849.7595, total_cost: 671250, usercpu_time_millis: 0.656, usercpu_time_millis_testing: 0.048, usercpu_time_millis_training: 0.608,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6245, average_cost: 16.7861, f_measure: 0.7564, kappa: 0.0053, kb_relative_information_score: -3139.844, mean_absolute_error: 0.273, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.821, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9747, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.9869, scimark_benchmark: 1849.3014, total_cost: 670570, usercpu_time_millis: 0.668, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 0.618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.622, average_cost: 16.8231, f_measure: 0.7555, kappa: 0.0017, kb_relative_information_score: -3172.658, mean_absolute_error: 0.274, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7953, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9781, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3698, root_relative_squared_error: 0.9881, scimark_benchmark: 1846.6923, total_cost: 672050, usercpu_time_millis: 0.613, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 0.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6203, average_cost: 16.8349, f_measure: 0.7553, kappa: 0.0006, kb_relative_information_score: -3240.1565, mean_absolute_error: 0.2744, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7926, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9796, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3701, root_relative_squared_error: 0.9888, scimark_benchmark: 1849.7595, total_cost: 672520, usercpu_time_millis: 0.608, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 0.557,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6251, average_cost: 16.7836, f_measure: 0.7565, kappa: 0.0056, kb_relative_information_score: -3120.6626, mean_absolute_error: 0.273, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8223, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9746, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.9868, scimark_benchmark: 1899.7086, total_cost: 670470, usercpu_time_millis: 0.659, usercpu_time_millis_testing: 0.046, usercpu_time_millis_training: 0.613,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6245, average_cost: 16.7883, f_measure: 0.7564, kappa: 0.0051, kb_relative_information_score: -3132.4638, mean_absolute_error: 0.2732, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8242, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9752, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3694, root_relative_squared_error: 0.987, scimark_benchmark: 1850.8185, total_cost: 670660, usercpu_time_millis: 0.644, usercpu_time_millis_testing: 0.044, usercpu_time_millis_training: 0.6,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1850.2875, total_cost: 672800, usercpu_time_millis: 0.394, usercpu_time_millis_testing: 0.044, usercpu_time_millis_training: 0.35,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1843.7819, total_cost: 672800, usercpu_time_millis: 0.415, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 0.368,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5768, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -818.808, mean_absolute_error: 0.2794, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9973, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3733, root_relative_squared_error: 0.9975, scimark_benchmark: 1846.1931, total_cost: 672800, usercpu_time_millis: 0.45, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 0.399,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1849.8294, total_cost: 672800, usercpu_time_millis: 0.428, usercpu_time_millis_testing: 0.046, usercpu_time_millis_training: 0.382,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5654, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -82.0514, mean_absolute_error: 0.28, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3741, root_relative_squared_error: 0.9998, scimark_benchmark: 1732.9037, total_cost: 672800, usercpu_time_millis: 0.45, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.401,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: 1.0609, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1735.0748, total_cost: 672800, usercpu_time_millis: 0.431, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.382,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6201, average_cost: 16.8349, f_measure: 0.7553, kappa: 0.0006, kb_relative_information_score: -3153.3223, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7926, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9799, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.37, root_relative_squared_error: 0.9888, scimark_benchmark: 1851.3986, total_cost: 672520, usercpu_time_millis: 0.596, usercpu_time_millis_testing: 0.049, usercpu_time_millis_training: 0.547,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

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From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs